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Reproducible microbenchmark for modeling domain crossing energy in heterogeneous compute systems.

0 starsPython

CrossingBench – Modeling when data movement dominates compute energy

by JessyMorissette·Feb 17, 2026·3 points·6 comments
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AI Analysis

●●SolidBig BrainNiche Gem

Rigorous energy model for domain crossings in chiplets and analog CIM systems.

Strengths
  • •Novel elasticity metric (ε) quantifies crossing dominance—not obvious framing
  • •Comprehensive cost model with sourced 7nm parameters, DOI-published methodology
  • •Pure Python, zero dependencies, reproducible sweep CLI designed for tweaking assumptions
Weaknesses
  • •Niche audience—only relevant for architects optimizing chiplet designs or analog systems
  • •Early stage: working paper not peer-reviewed, small GitHub activity suggests pre-launch
  • •Limited empirical validation—relies on published parameters, not new measurements
Target Audience

Computer architects, systems researchers, heterogeneous computing engineers

Post Description

I built a small reproducible microbenchmark exploring when system energy becomes dominated by boundary crossings rather than intra-domain compute.

The model decomposes total energy into: C = C_intra + Σ V_b · c_b

Includes:

CLI sweeps

Elasticity metric (ε) as a dominance indicator

CSV outputs

Working draft paper

*DOI

Looking for critique, counter-examples, or prior related work I may have missed.

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